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The VEGA CPAP System/Heated Humidifier, models CP-03 delivers positive airway pressure therapy for the treatment of Obstructive Sleep Apnea only. The device is intended for use in the home or hospital/institutional environment on adult patients.

The VEGA CPAP System/Heated Humidifier, models CP-03 is a smaller and lighter AC -powered, micro processor-controlled, and blower-based system that generates positive airway pressure from 3 to 20 cm H2O. The device is intended for use with a patient circuit that is used to connect the device to the patient interface(mask). The CPAP device may also be used with VEGA Heated Humidifier that has been designed to be compatible with the CPAP and controlled from the CPAP. The basic functional and performance characteristics of the VEGA CPAP System/Heated Humidifier are completely similar to the predicate device, the Respironics REMstar Plus CPAP System/REMstar Heated Humidifier(K010263).

The provided text does not contain information about acceptance criteria or a study proving that a device meets such criteria in the context of a medical device's performance characteristics or clinical outcomes. Instead, it describes a 510(k) summary for a CPAP system and heated humidifier, focusing on its substantial equivalence to a predicate device, technical specifications, and non-clinical verification activities.

Specifically:

• The document mentions "Performance Compliance Test for CPAP according to ISO 17510-1" and "Performance Compliance Test for heated humidifier according to ISO 17510-1" as non-clinical tests conducted by the manufacturer. However, it does not specify what the acceptance criteria for these tests were (e.g., specific pressure accuracy ranges, flow rate tolerances, temperature stability) nor does it report the device's performance against any such criteria.
• It explicitly states: "No any Clinical Test is conducted for the VEGA CPAP System/Heated Humidifier." This means there is no clinical study to demonstrate effectiveness or patient outcomes, which would typically be associated with acceptance criteria for device performance in a clinical setting.
• The document primarily relies on "substantial equivalence" to a predicate device (Respironics REMstar Plus CPAP System/REMstar Heated Humidifier, K010263) based on similar intended use and technological characteristics, and verification/validation tests for electrical safety and EMC.

Therefore, I cannot provide the requested table or answer most of the questions because the necessary information (acceptance criteria, reported performance against those criteria, details of a performance study, sample sizes, ground truth, expert qualifications, etc.) is not present in the provided 510(k) summary.

In summary, the document does not describe a study that proves the device meets specific acceptance criteria in the way a clinical trial or a detailed performance validation report would.

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The Infrared Ear Thermometer, models IR-04MT are the battery-operated electronic devices with intended use of measuring body temperature from the auditory canal of a patient by means of an infrared sensor coupled with electronic signal amplification, conditioning and a digital LCD(display) unit. The device is a reusable and intended for home use on people at all ages.

The Infrared Ear Thermometer, models IR-04MT is a handheld electronic thermometers that measures the temperature through the opening of the auditory canal by using a thermopile as the temperature sensor. The signal of sensor is calculated and displayed by an ASIC (Application Specific IC) – controlled circuit, which is considered the hard-wire control instead of programmable control.

From the construction point of view, the ear thermometer comprises of a thermopile for the measuring sensor, a reference thermistor for comparison of temperature, a buzzer for sounding effect, an ASIC for calculating, and LCD for displaying the measuring temperature digitally for which the thermopile sensor detect the ear canal temperature through the infrared.

This system uses a 3.0 V DC battery(2xAAA batteries) for operation of complete system whenever the battery is low, the ASIC circuit will detect the low battery condition automatically, and displays 'Low battery' in LCD display. Regarding the performance of IR-04MT, they were designed and verified according to the US standard ASTM E 1965-2003.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Infrared Ear Thermometer, models IR-04MT:

1. Table of Acceptance Criteria and Reported Device Performance

Despite multiple references to performance and compliance with ASTM E1965-2003, the document does not explicitly state specific numerical acceptance criteria for accuracy (e.g., a specific deviation tolerance) or the exact reported performance metrics from the clinical study in an easily quantifiable format. It broadly states the device "was designed and verified according to the US standard ASTM E 1965-2003" and that "The results of the Clinical Test Report could positively support the claim of Substantial Equivalence."

To fulfill this section accurately, I can only infer the acceptance criteria are met by compliance with the referenced standard.

2. Sample Size Used for the Test Set and Data Provenance

• Test Set Sample Size: Not explicitly stated. The document mentions "A Clinical Test Report conducted according to ASTM E1965:2003" but does not provide the number of subjects or measurements included in this test.
• Data Provenance: The study was conducted by the "manufacturer," which is DONGGUAN DALANG VIGOR ELECTRONICS MFY in China. Therefore, the data provenance is China. It is a prospective study, as it was a "Clinical Test Report conducted... performed by the manufacturer" as part of the device's validation.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• The document does not provide information on the number or qualifications of experts used to establish ground truth. The nature of an ear thermometer's ground truth (e.g., a reference rectal or oral temperature measured by a calibrated clinical thermometer) typically doesn't involve "experts" in the sense of radiologists or pathologists. Instead, it relies on the accuracy of the reference device and the methodology for its use.

4. Adjudication Method for the Test Set

• The document does not mention any adjudication method. For a device like an ear thermometer, "adjudication" in the traditional sense of multiple reviewers resolving discrepancies is not typically applicable. The ground truth is generally a single, objectively measured value from a reference method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

• No, an MRMC comparative effectiveness study was not done. This type of study (MRMC) is relevant for diagnostic imaging devices where human readers interpret medical images, sometimes with AI assistance. The Infrared Ear Thermometer is a direct measurement device, not an interpretative one, and does not involve AI assistance for human readers.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, this is effectively a standalone performance study. The device itself is an "algorithm only" (ASIC-controlled circuit) device that measures and displays temperature. Human involvement is limited to operating the device (placing it in the ear canal and reading the display), not interpreting complex output that would require a "human-in-the-loop" interaction in the typical sense of AI-assisted diagnostics. The clinical test measured the device's accuracy against a recognized standard without a human interpretation component that would require comparison to human-in-the-loop scenarios.

7. The Type of Ground Truth Used

• The ground truth used would be a reference temperature measurement obtained by a calibrated clinical thermometer following the guidelines of ASTM E1965:2003. This standard details how to conduct clinical performance evaluations for infrared thermometers. It implies a direct comparison to a known accurate temperature measurement from a standard clinical method (e.g., a rectal thermometer) under controlled conditions.

8. The Sample Size for the Training Set

• The document does not mention a specific training set or its sample size. This device is described as having an "ASIC (Application Specific IC) – controlled circuit," which is a "hard-wire control instead of programmable control." This implies a fixed, hardware-based algorithm rather than a software algorithm that would undergo a separate "training" phase with a dataset. Therefore, the concept of a "training set" as understood in machine learning/AI (which wasn't the focus of this device) does not apply here.

9. How the Ground Truth for the Training Set Was Established

• As there is no indicated "training set" in the context of an ASIC-controlled, hard-wired device that is not an AI/machine learning product, this question is not applicable. The device's fundamental function is governed by its hardware design and integrated circuit, which are designed to comply with physical principles of thermometry.

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The VEGA Medical Suction Equipment, model SU-01/SU-DC01 is a device used to remove fluids from airway or respiratory support system and infectious materials from wounds.

The VEGA Medical Suction Equipment, model SU-01/SU-DC01 is a portable AC powered suction pump. It consists of a pump unit, collection bottle, relief valve, vacuum gage, bacteria filter, and suction tube. The device is designed and manufactured to comply with IEC 60601-1. IEC 60601-1-2, and ISO 10079-1.

The provided text describes the 510(k) premarket notification for the "VEGA Medical Suction Equipment, model SU-01/SU-DC01." However, it does not include information about acceptance criteria or a study that proves the device meets those criteria, as typically understood for AI/algorithm-based devices with performance metrics like sensitivity, specificity, etc.

Instead, this submission is for a medical suction pump, which is a hardware device. The "acceptance criteria" and "study" described are about demonstrating substantial equivalence to a predicate device and compliance with relevant safety and performance standards for such hardware.

Here's a breakdown based on the provided text, addressing your points where applicable for this type of device:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly present a table of acceptance criteria for performance metrics in the typical sense (e.g., sensitivity, specificity, accuracy). Instead, acceptance criteria are inferred from the compliance with international standards and comparison to the predicate device.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

This information is not applicable in the context of this 510(k) submission for a medical suction pump. The "tests" mentioned are compliance tests against engineering standards, not performance evaluations on a patient "test set" with data in the way AI/software devices are evaluated.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This information is not applicable. Ground truth, as typically discussed for medical AI/imaging, is not relevant for the compliance testing of a hardware medical suction pump. Compliance is against defined engineering standards.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

This information is not applicable. Adjudication methods are used in scenarios where human interpretation or consensus is required to establish ground truth from complex medical data (e.g., images, clinical records). This is not the case for a hardware device's compliance testing.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

This information is not applicable. This type of study investigates the impact of AI on human reader performance, which is not relevant for a standalone medical suction device. The submission explicitly states: "No particular Clinical Test was conducted for VEGA Medical Suction Equipment."

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This information is not applicable. This device is a physical medical suction equipment, not an algorithm. Therefore, "standalone algorithm performance" is not a relevant concept for this submission.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

This information is not applicable. The "truth" for this device's evaluation is compliance with established engineering and safety standards (ISO 10079-1, IEC 60601-1, IEC 60601-1-2) and demonstration of substantial equivalence to a predicate device based on its design and specifications.

8. The sample size for the training set

This information is not applicable. There is no "training set" as this is a hardware device, not a machine learning model.

9. How the ground truth for the training set was established

This information is not applicable. As there is no training set, there is no ground truth to establish for it.

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The Digital Thermometer, models MT-XX8 and MT-XX9 are the battery-operated electronic devices with intended use of measuring human body temperature precisely. It can be measurement of oral, axially and rectal temperature.

The Digital Thermometers, models MT-XX8 and MT-XX9, are the electronic themometers by using a thermistor as the temperature sensor. The signal of sensor is calculated and displayed by an ASIC (Application Specific IC) control instead of programmable control. Basically MT-XX8 and MT-XX9 have the same control and only the different measuring range caused by some small different design in IC circuit. From the construction point of view, the digital thermometer comprises of a thermistor for measuring sensor, a reference resistor for comparison of temperature, a buzzer for sounding effect, an ASIC for calculating, and LCD for displaying the measuring temperature digitally for which the thermistor contacts. This system uses a 1.5V DC battery for operation of complete system whenever the battery is low, the ASIC circuit will detect the low battery condition automatically, and displays 'Low battery' in LCD display.

The provided text describes the submission for a 510(k) premarket notification for the VEGA TECHNOLOGIES, INC. Digital Thermometers, models MT-XX8 and MT-XX9. It focuses on demonstrating substantial equivalence to a predicate device and compliance with relevant standards, rather than providing detailed acceptance criteria and a comprehensive study report with the specific information requested.

Therefore, many of the requested details cannot be extracted from the given document.

Here's an attempt to answer what can be inferred:

1. A table of acceptance criteria and the reported device performance

The document states that the performance of MT-XX8 and MT-XX9 was "designed and verified according to the US standard ASTM E1112-98". This standard sets the acceptance criteria for electronic thermometers. However, the specific values for the acceptance criteria from ASTM E1112-98 (e.g., accuracy ranges) and the reported device performance directly measured against these criteria are not present in the provided text. The text only says it was "designed and verified according to" the standard.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document. The document mentions "verification and validation tests contained in this submission," but does not detail the sample size, type of test set (e.g., human subjects, calibration blocks), or data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not provided. For a digital thermometer, "ground truth" would typically be established by a highly accurate reference thermometer in a controlled environment, not by human experts in the way it would be for image analysis.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not applicable to this device. This type of study is typically used for AI-powered diagnostic tools where human readers (e.g., radiologists) interpret cases with and without AI assistance. The described device is a standalone electronic thermometer, not an AI-assisted diagnostic tool.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, a standalone performance assessment was conducted in the sense that the device's accuracy was "designed and verified according to the US standard ASTM E1112-98." This standard dictates performance testing of the device itself, independent of human interpretation or involvement beyond operating the device. However, specific performance metrics are not listed.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

For a digital thermometer, the ground truth would typically be established using calibrated reference thermometers and controlled temperature environments, in accordance with standards like ASTM E1112-98. The document does not explicitly state this, but it is implied by the reference to the standard.

8. The sample size for the training set

This information is not provided. The device is an electronic thermometer controlled by an ASIC (Application Specific Integrated Circuit) with hard-wired control, not a machine learning or AI algorithm that requires a "training set" in the conventional sense.

9. How the ground truth for the training set was established

As explained in point 8, the concept of a "training set" and "ground truth for training" as typically used for AI algorithms is not applicable to this device. Its function is based on thermistor physics and established electronics, not a learnable model. The design and verification would rely on fundamental engineering principles and calibration against known temperature standards.

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The VigorMist Compressor is intended to be used with a compatible pneumatic nebulizer (specifically the W estMed V ixOne) t o c onvert c ertain inhalable drugs into an aerosol form for inhalation by a patient for the treatment of asthma, COPD, and other respiratory ailments. The device is intended for the home care market. It is intended for use with a single adult, pediatric, or infant patient.

The VigorMist™ Compressor is a small air compressor designed to provide sufficient air pressure and flow to power a hand held nebulizer. It measures 11 7/8" x 7 1/8" x 4 1/2" and weights 4.6 lbs.

The device has a thermal protector that will automatically shut off the device when overheated. The operating components are located internally. The compressor, some minor wiring and exhaust/intake tubing are located inside .. External components include a switch, filter with housing, AC cord and cover or accessories compartment. The accessories coming with the compressor include a nebulizer, Air tube and mouthpiece.

The provided information for the VigorMist Compressor Nebulizer (K031413) primarily focuses on its intended use, description, and regulatory details for a 510(k) submission. It does not include detailed studies or data proving specific acceptance criteria in the way a modern AI/software device submission would.

Based on the provided text, I can infer some general acceptance criteria for a medical device like this (e.g., performance specifications, biocompatibility, standards conformity), but the document does not present quantitative metrics or specific study designs to demonstrate these.

Here's an attempt to structure the information based on your request, highlighting what is present and what is conspicuously absent:

Acceptance Criteria and Device Performance for VigorMist Compressor Nebulizer (K031413)

The provided 510(k) summary for the VigorMist Compressor Nebulizer (K031413) indicates that the device underwent testing to ensure it met performance specifications and regulatory requirements. However, the document does not present specific quantitative acceptance criteria or detailed results of a study designed to demonstrate performance against those criteria in a format typical for complex AI or diagnostic devices.

Instead, the submission states that "The VigorMist™ successfully completed testing and demonstrates that the product fulfills performance specifications." This indicates that some form of internal validation was conducted, likely against engineering and safety standards.

1. Table of Acceptance Criteria and Reported Device Performance

Regarding the Study That Proves the Device Meets Acceptance Criteria:

The document refers to "Performance Testing" but does not describe a clinical study or a detailed technical study with the characteristics requested (sample size, ground truth, expert adjudication, etc.). This submission is for a Compressor Nebulizer, a relatively simple electro-mechanical device, and the regulatory pathway in 2003 for such devices generally relied on demonstrating substantial equivalence to predicates through engineering testing and adherence to recognized standards, rather than large-scale clinical trials or AI-specific validation studies.

Here's what can be inferred or explicitly stated from the document in response to your specific questions:

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: Not applicable in the context of what is provided. The document refers to "testing," but it's likely referring to bench testing, engineering validation, and standards conformity for the device hardware itself, not a test set of data like one would use for an AI algorithm.
• Data Provenance: Not applicable.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

• Number of Experts: Not applicable. Ground truth, in the sense of expert consensus on medical images or patient outcomes, is not relevant to the type of testing described for this device.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of AI Assistance

• MRMC Study: No. This type of study is not relevant for a compressor nebulizer.
• Effect Size of AI Improvement: Not applicable, as there is no AI component mentioned.

6. If a Standalone (Algorithm Only) Performance Study Was Done

• Standalone Study: No. This device is a hardware compressor; it does not contain an algorithm in the sense of a software-based diagnostic or analytical tool.

7. The Type of Ground Truth Used

• Type of Ground Truth: For a compressor nebulizer, "ground truth" would relate to engineering specifications (e.g., precise measurements of air pressure, flow rate, aerosol particle size distribution determined by calibrated instruments, and compliance with safety standards). The document states testing was completed for "biocompatibility, standards conformity," and "performance specifications," indicating these were the basis for demonstrating quality and safety.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This device is not an AI/ML algorithm that requires a training set.

9. How the Ground Truth for the Training Set Was Established

• Ground Truth for Training Set: Not applicable.

Conclusion:

The provided 510(k) summary for the VigorMist Compressor Nebulizer (K031413) serves as a regulatory document demonstrating substantial equivalence to predicate devices, focusing on the device's design, intended use, and a general statement of successful completion of performance, biocompatibility, and standards conformity testing. It does not contain the detailed study descriptions, quantitative acceptance criteria, or ground truth methodologies that would be expected for a modern AI-powered diagnostic device submission, as it is a mechanical device.

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